Why use artificial intelligence for HR automation?
“AI is an accelerator – it allows us the ability to ingest a variety of data and provide context to a decision maker or employee or business leader. It allows us to deliver the right intelligence in the moment and achieve personalization at scale.” – Tom Stachura, Vice President Talent Solutions & People Analytics, IBM
Artificial intelligence and HR may seem antithetical, and this seemingly unlikely yet increasingly common partnership between AI and HR can often cause public dialogue around artificial intelligence and workflow automation to hit its more feverish pitches. Realistically, HR departments deal with a high-volume of data transactions on a daily basis, many of which involve manual data entry, hopping between SaaS apps to complete work, and performing repetitive administrative tasks.
AI tools can enhance the human power of the HR department, allowing employees to make more informed decisions, hire the right candidates more quickly and efficiently, and scale processes without decreasing the quality of employee service and departmental decision-making. Automating workflows and supplementing workflows with AI frees up time and energy for HR to focus more on the tasks which humans need, and excel at, the most- creating workplace culture, devoting their time to creative problem-solving, and designing effective strategies.
Today: HR Automations help high-growth companies scale hiring processes
When your company is hitting “hockey stick growth”, you’re going to be hiring at an unprecedented rate. HR teams can quickly become swamped with applications as they work to standardize hiring practices across the organization and scale processes for the future. This is the ideal time to think about automating repetitive processes within the HR department.When your company is hitting “hockey stick growth”, you’re going to be hiring at an unprecedented rate, and HR can get overwhelmed. This is the time to automate repetitive business processes to enable your organization to scale. Click To Tweet
So, how are companies using the power of AI in HR processes today?
Using Image-Parsing AI for Competitive Wage Research
A leading worldwide retailer was using local job postings to research retail wages in the specific geographic areas around its stores. Their process was originally to have employees in the HR department research job postings and manually enter the data from competitors into the HR database. They would also have employees email photos of job listings to the HR department, and then the HR team would manually enter the data from these photos into the HR database. There was significant lag time in getting the information into the database for use and analysis, because the process took so long. There had to be a better way.
The company switched to using ParseHub to scrape the web for wage data from job postings in the geographic area of the store. Now, ParseHub gathers the data and a workflow automation sends it to the HR database in real-time, eliminating the lag time in processing the information. Additionally, employees can now text or email an image of a job posting to Twilio, which is retrieved from Twilio or email and sent to Google Cloud Vision via automation to convert the information in the .jpeg into usable data. The automation then sends the data to the HR database.
This automation reduces manual data entry for the HR department, saves time, and keeps their competitive wage analysis up to date by reducing the time it takes to process data gathered from local jobs listings. A small difference in hourly wage can be enough for an hourly employee to leave their job for a competitor, so having accurate competitive wage analysis is important for employee retention.
Lead Enrichment for Following up with Applicants from Job Fairs
Employers can use Google Cloud Vision and a program like Clearbit to enrich data for potential candidates. First, the employer can send a photo of a business card or job fair badge to a Twilio number. The image is then taken to Google Cloud Vision, parsed, and the information is sent through Clearbit. Clearbit provides, within a matter of minutes, a much more comprehensive set of data on the potential candidate, such as past jobs or additional contact information.
Natural Language Processing for Employee Helpdesk
Employers can create an automated employee helpdesk that uses natural language processing to answer common questions and concerns for their employees. For example, new employees may have questions about who to contact for equipment difficulties, how to request PTO and other common questions. This often falls on individual managers to field when these questions are often addressed in company handbooks and other knowledge sources. An automated helpdesk on the other hand, can serve answers quickly through a chat application such as Slack or Microsoft Teams without draining your resources on internal education.
Automating a chat helpdesk can continue serving employees long after they are onboarded. Tenable, a solutions provider for cyber exposure, needed employees ranging from engineers to sales reps and support agents, to be able to access technical product information in a timely manner. Information such as updates on their latest product release are stored in their CRM and ITSM knowledge bases. They wanted a solution that would make the information available to employees through a bot on Slack. So, they created a bot-based automated workflow, which employees can use to ask questions. The bot serves the employee the right articles from the central knowledge base to answer their questions and has a built in workflow to manage exceptions (ie. when the bot cannot answer the question).
Parse and Sort Data from Resumes with DocParser
HR professionals are often tasked with scanning resumes, which are each organized differently depending on the applicant’s individual organization and design choices, and manually entering data from resumes into the HR application or database. However, parsing images to eliminate manual data entry is an area where AI excels.
Instead, companies can extract relevant data from applicant’s resumes using DocParser, then automatically create a pre-hire account in Workday or other HR apps. The automation maps applicant data into the appropriate fields, and sends a notification to the appropriate team members in Slack. Team members can indicate whether or not they wish to continue the hiring process with a given applicant by clicking a button in Slack. The process is secure, because the automation uses Verified User Access, a proprietary security technology for approval workflows.
To parse resumes automatically from incoming emails, you can set up an automated workflow that downloads email attachments and uploads the file to Box. Then, the automation gets the file download URL from Box and fetches the document from the URL in DocParser.
The Future: Creating a Meaningful Work Environment with AI-Enabled HR Automations
A meaningful work environment is crucial for employee satisfaction and retention. A recent survey by Future Workplace reports that having a view of or proximity to nature- things like natural light or a view of a park- are far more fundamentally important to employees than things like free snacks and happy hours, or other trendy perks. Although it’s hard to bring employees to nature using technology, unless you want to have everyone working from a VR headset, companies could find another route toward increasing employee satisfaction, by using data insights to collect information on employee performance, and potentially open up opportunities for high-performing employees who want to be on an internal growth track.
Using performance data for decision making
Adi Gaskell notes in an article for Forbes that there is an enormous quantity of performance data collected on football players, and other star athletes. Their performance is scrutinized and quantified any time they set foot on the field. Could these types of quantifiable statistics about employees be used to increase workplace satisfaction and situate employees in a working environment that’s most suited to their preferences?
Gaskell notes, “Suffice to say, professional football, and perhaps sport in general, is relatively unique in terms of the amount of performance data created by athletes. This presents scientists with the opportunity to use AI tools like this to provide decision support to coaches. At the moment, HR managers don’t have anywhere near as much data available on the performance of staff, but these projects provide a glimpse into the possibilities should such data ever become available.”
Using data management to create opportunities for internal growth
Implementing increased data management about employee performance and interests may make it easier for HR to identify high-performing employees who want to be on a growth track toward leadership at their organization. There is a common cultural trope that companies have a tendency to overpay outside hires, and leave internal employees waiting years for advancement without seeing it manifest. Unfortunately, some of these tropes are actually true.
- Outside hires receive lower performance evaluations for the first two years in their role than their counterparts who are promoted internally.
- Outside hires are more likely to leave, and they are paid “substantially [18-20%] more.”
- Outside hires (if they stay more than two years), get promoted faster than those who are promoted from inside.
Harvard Business Review reports that they “surveyed over 400,000 U.S. workers in the past year and found that when people believe promotions are managed effectively, they’re more than twice as likely to give extra effort at work and to plan a long-term future with their company.” HBR continues that when employees believe that their company is managing promotions effectively, they’re also “five times as likely to believe leaders act with integrity,” revealing that managerial decisions about internal growth can strengthen- or jeopardize- employee loyalty and trust between employees and management.
At large corporations where hundreds of employees work in each of the hundreds of departments and locations, this is an area where companies may look to data management and AI in order to track employee growth and preferences, offer internal training and education opportunities, and create opportunities for more effective and objective performance monitoring.
When to exercise caution with AI-Enabled tools for HR
Companies that choose to implement performance tracking should be mindful that the purpose of this technology is not to institute a Fouccaultian surveillance state, or to extract efficiency from employees at the expense of corporate culture and human wellness. On the contrary, it is best deployed as a method for improved understanding between managers and employees, and a platform to track and strive toward mutual progress. After all, if employees are forbidden from thriving and developing at a natural pace, they will leave, and your organization will struggle to retain engaged, experienced, high-value employees.
Additionally, some machine learning (ML) technology has proven itself ineffective and biased at some, but not all, facets of candidate screening for the hiring process. Machine learning differs from more traditional forms of computing that rely on rule-based logic. ML has been designed to process input in a different way, by identifying patterns from large data sets. Unfortunately, this computing method imprints and deepens statistical bias against individuals who don’t meet an “objective” ideal determined by group trends.
But overall, better technology can make for a better employee experience, from day one, and throughout their career with the company.
Fab Capodicasa, CEO of Hoosh Marketing, notes that you can automate recruiting without scaring candidates away. He describes how, overall, the automated process at Hoosh has been more fair to applicants than manual screening: “We have manual processes baked in because there are sometimes qualified candidates that get rejected or unqualified candidates that get passed through, but those happen less frequently now than when our recruitment process was entirely manual.”
Implementing AI-Enabled HR Automations to Improve Efficiency and Employee Experience
With or without AI, there are a wide range of HR automations that are robust and ready for use.
Hire to retire automations are a popular process to automate because it improves employee experience and saves companies time and money.
Workato is an enterprise automation platform that makes it possible these automations, and many more, to leverage the power of AI in automated business processes.
Workato’s secure platform for creating and deploying cloud-based application integrations and enterprise automations is easy to use, with a drag-and-drop interface that employees with little to no engineering background can master.
To learn more about how to use this platform to automate HR processes at your organization, request a demo from our team, or check out our free ebook on accelerating digital transformation.